JPMorgan Applied AI ML Associate 

United States, New York, New York 

669645712

As an Applied AI ML Associate within our innovative AI team, you will be tasked with the development, testing, containerization, and deployment of machine learning applications and models to cloud infrastructure. We are in search of a team member with a strong understanding of source control, robust testing, deployment processes, containerization, cloud, and ML techniques and frameworks. You will collaborate closely with other team members to create modular and scalable code using object-oriented programming concepts in Python, and work together using version control systems.

Job responsibilities

• Find automation opportunities gathering business knowledge from stakeholders, exploring large volumes of complex data, and testing hypothesis using traditional and cutting-edge machine learning models.
• Partner with different parts of the business, understanding key challenges and metrics of success, communicating results, and gathering feedback to improve model performance and expectations.
• Build machine learning models and deploy these models following all relevant processes and governance.

Required qualifications, capabilities and skills

• Recent PhD degree or MS degree with experience in the application of AI/ML to a relevant field
• Solid programming skills with Python, R, or other equivalent languages, and experience using frameworks as Scikit-Learn.
• Strong mathematical and statistical skills, including knowledge of exploratory data analysis, statistical models, GLM, decision trees, clustering, bootstrapping.
• Ability to identify model and data issues, then propose, prototype, and evaluate alternatives, prioritizing the business benefits rather than the trendiness of the solution.
• Curiosity exploring large and complex datasets, extracting big picture insights as well as identifying critical low-level details.
• Great communication and presentation skills that enable collaboration and transparency with non-technical senior leaders as well as technical counterparts.
• Self-motivation and comfortable working with a geographically distributed team.